.. DO NOT EDIT. .. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY. .. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE: .. "auto_examples/plot_profiling.py" .. LINE NUMBERS ARE GIVEN BELOW. .. only:: html .. note:: :class: sphx-glr-download-link-note Click :ref:`here <sphx_glr_download_auto_examples_plot_profiling.py>` to download the full example code .. rst-class:: sphx-glr-example-title .. _sphx_glr_auto_examples_plot_profiling.py: .. _l-example-profiling: Profile the execution of a simple model ======================================= *ONNX Runtime* can profile the execution of the model. This example shows how to interpret the results. .. GENERATED FROM PYTHON SOURCE LINES 14-32 .. code-block:: default import onnx import onnxruntime as rt import numpy from onnxruntime.datasets import get_example def change_ir_version(filename, ir_version=6): "onnxruntime==1.2.0 does not support opset <= 7 and ir_version > 6" with open(filename, "rb") as f: model = onnx.load(f) model.ir_version = 6 if model.opset_import[0].version <= 7: model.opset_import[0].version = 11 return model .. GENERATED FROM PYTHON SOURCE LINES 33-34 Let's load a very simple model and compute some prediction. .. GENERATED FROM PYTHON SOURCE LINES 34-45 .. code-block:: default example1 = get_example("mul_1.onnx") onnx_model = change_ir_version(example1) onnx_model_str = onnx_model.SerializeToString() sess = rt.InferenceSession(onnx_model_str, providers=rt.get_available_providers()) input_name = sess.get_inputs()[0].name x = numpy.array([[1.0, 2.0], [3.0, 4.0], [5.0, 6.0]], dtype=numpy.float32) res = sess.run(None, {input_name: x}) print(res) .. rst-class:: sphx-glr-script-out Out: .. code-block:: none [array([[ 1., 4.], [ 9., 16.], [25., 36.]], dtype=float32)] .. GENERATED FROM PYTHON SOURCE LINES 46-48 We need to enable to profiling before running the predictions. .. GENERATED FROM PYTHON SOURCE LINES 48-60 .. code-block:: default options = rt.SessionOptions() options.enable_profiling = True sess_profile = rt.InferenceSession(onnx_model_str, options, providers=rt.get_available_providers()) input_name = sess.get_inputs()[0].name x = numpy.array([[1.0, 2.0], [3.0, 4.0], [5.0, 6.0]], dtype=numpy.float32) sess.run(None, {input_name: x}) prof_file = sess_profile.end_profiling() print(prof_file) .. rst-class:: sphx-glr-script-out Out: .. code-block:: none onnxruntime_profile__2022-03-16_00-27-12.json .. GENERATED FROM PYTHON SOURCE LINES 61-63 The results are stored un a file in JSON format. Let's see what it contains. .. GENERATED FROM PYTHON SOURCE LINES 63-71 .. code-block:: default import json with open(prof_file, "r") as f: sess_time = json.load(f) import pprint pprint.pprint(sess_time) .. rst-class:: sphx-glr-script-out Out: .. code-block:: none [{'args': {}, 'cat': 'Session', 'dur': 68, 'name': 'model_loading_array', 'ph': 'X', 'pid': 3028, 'tid': 3028, 'ts': 1}, {'args': {}, 'cat': 'Session', 'dur': 194, 'name': 'session_initialization', 'ph': 'X', 'pid': 3028, 'tid': 3028, 'ts': 86}] .. rst-class:: sphx-glr-timing **Total running time of the script:** ( 0 minutes 0.006 seconds) .. _sphx_glr_download_auto_examples_plot_profiling.py: .. only :: html .. container:: sphx-glr-footer :class: sphx-glr-footer-example .. container:: sphx-glr-download sphx-glr-download-python :download:`Download Python source code: plot_profiling.py <plot_profiling.py>` .. container:: sphx-glr-download sphx-glr-download-jupyter :download:`Download Jupyter notebook: plot_profiling.ipynb <plot_profiling.ipynb>` .. only:: html .. rst-class:: sphx-glr-signature `Gallery generated by Sphinx-Gallery <https://sphinx-gallery.github.io>`_